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Syn-MolOpt: a synthesis planning-driven molecular optimization method using data-derived functional reaction templates

delete2025-03-02
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OA
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X
Xiaodan Yin
王小蕊 cover
王小蕊 (Xiaorui Wang)
吴振兴 cover
吴振兴 (Zhenxing Wu)
Q
Qin Li
Y
Yu Kang
Y
Yafeng Deng
罗培 (Pei Luo)
H
Huanxiang Liu
G
Guqin Shi
W
Wang, Zheng
X
Xiaojun Yao *
C
Chang‐Yu Hsieh
侯廷军 (Tingjun Hou) *
DOI:10.1186/s13321-025-00975-9delete
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Abstract

Abstract

En 中文
Molecular optimization is a crucial step in drug development, involving structural modifications to improve the desired properties of drug candidates. Although many deep-learning-based molecular optimization algorithms have been proposed and may perform well on benchmarks, they usually do not pay sufficient attention to the synthesizability of molecules, resulting in optimized compounds difficult to be synthesized. To address this issue, we first developed a general pipeline capable of constructing functional reaction template library specific to any property where a predictive model can be built. Based on these functional templates, we introduced Syn-MolOpt, a synthesis planning-oriented molecular optimization method. During optimization, functional reaction templates steer the process towards specific properties by effectively transforming relevant structural fragments. In four diverse tasks, including two toxicity-related (GSK3 beta-Mutagenicity and GSK3 beta-hERG) and two metabolism-related (GSK3 beta-CYP3A4 and GSK3 beta-CYP2C19) multi-property molecular optimizations, Syn-MolOpt outperformed three benchmark models (Modof, HierG2G, and SynNet), highlighting its efficacy and adaptability. Additionally, visualization of the synthetic routes for molecules optimized by Syn-MolOpt confirms the effectiveness of functional reaction templates in molecular optimization. Notably, Syn-MolOpt's robust performance in scenarios with limited scoring accuracy demonstrates its potential for real-world molecular optimization applications. By considering both optimization and synthesizability, Syn-MolOpt promises to be a valuable tool in molecular optimization.Scientific contribution Syn-MolOpt takes into account both molecular optimization and synthesis, allowing for the design of property-specific functional reaction template libraries for the properties to be optimized, and providing reference synthesis routes for the optimized compounds while optimizing the targeted properties. Syn-MolOpt's universal workflow makes it suitable for various types of molecular optimization tasks.
Keywords:
Molecular optimization
Synthetic planning
Reaction template
Toxicity optimization
Metabolic property optimization
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Journal of Cheminformatics cover
Journal of Cheminformatics
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liangzhu laboratory
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Macao Polytechnic University
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zhejiang university
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